Infrared Image Segmentation Based on Improved Dimensional OTSU and Genetic Algorithm

doi:10.16182/j.issn1004731x.joss.201706010

Abstract

Abstract: In order to improve the image segmentation of circuit board, and solve the problem of circuit board fault diagnosis, a new algorithm combines adaptive genetic algorithm and improved two-dimensional OTSU algorithm was proposed. a fast sorting method, in accordance with changes in the genetic algebraic, crossover and mutation probability was improved; according to the distance between the center and neighboring pixels pixel for the neighborhood average algorithm to weight the scale factor, on the basis of judgment on noise point of thermal infrared image to reduce noise; and introduced into the class variance method to solve the equation for the threshold to optimize. The new algorithm uses a genetic algorithm parallelism and powerful spatial search capability, improving dimensional OTSU threshold search speed and improving the efficiency of thermal infrared image segmentation. Experimental results show that the algorithm improves the accuracy of thermal infrared image segmentation, there are certain applications.

Key words: adaptive genetic algorithm, two-dimensional OTSU, thermal infrared image, circuit boards

CLC Number:

TP391.9

Wang Kun, Zhang Yang, Song Shengbo, Zhuge Jingchang. Infrared Image Segmentation Based on Improved Dimensional OTSU and Genetic Algorithm[J]. Journal of System Simulation, 2017, 29(6): 1229-1236.

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